Translating and Rewriting Chinese Proverbs: A Case Study of Howard Goldblatt’s English Translation of Mo Yan’s “Shengsi Pilao”
Bibliographic record
Abstract
Howard Goldblatt’s translation of Mo Yan’s novels remains controversial because he has made various changes in his translation. As a result, a lot of original messages in Mo Yan’s novels were not completely conveyed. In this paper, this author compared and analyzed several examples of Chinese proverbs selected from Mo Yan’s novel “Shengsi Pilao” and their translation in “Life and Death Are Wearing Me Out” translated by Howard Goldblatt, in an attempt to investigate how Goldblatt coped with linguistic and cultural challenges in the examples. Findings indicate that based on rewriting, Goldblatt has basically used six translation methods to translate Mo Yan’s Chinese proverbs in the novel into English and his transcreation which was previously neglected can be uncovered in his translation of the proverbs. This study can help other translators reflect on how to translate proverbs in other Chinese literary works into English and provide valuable references to researchers who intend to conduct research into this area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".